1. CS 405G: Introduction to Database Systems
Relations 1

2. Topics Next Case study on ER Model Conversion of ER models to Schemas
Reading Assignment
Chapter 5.1, 5.2
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3. ER Case study
Design a database representing cities, counties, and states
For states, record name and capital (city)
For counties, record name, area, and location (state)
For cities, record name, population, and location (county and state)
Assume the following:
Names of states are unique
Names of counties are only unique within a state
Names of cities are only unique within a county
A city is always located in a single county
A county is always located in a single state
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4. Case study : first design
County area information is repeated for every city in the county
Redundancy is bad.
What else?
State capital should really be a city
Should “reference” entities through explicit relationships
name
name In
Cities
States
population
capital
county_name
county_area
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5. Case study : second design
Technically, nothing in this design could prevent a city in state X from being the capital of another state Y, but oh well…
name
Cities
population In
IsCapitalOf
name In
Counties
States
name
area
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6. Review
A data model is
a group of concepts for describing data.
What are the two terms used by ER model to describe a miniworld?
Entity
Relationship
What makes a good database design
Student (sid: string, name: string, login: string, age: integer, gpa:real)
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7. Database Design
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8. A Relation is a Table
name manf Winterbrew Pete’s Bud Lite Anheuser-Busch Beers
Attributes
(column
headers)
Tuples
(rows)

9. Schemas
Relation schema = relation name + attributes, in order (+ types of attributes).
Example: Beers(name, manf) or Beers(name: string, manf: string)
Database = collection of relations.
Database schema = set of all relation schemas in the database.

10. Why Relations? Very simple model.
Often matches how we think about data.
Abstract model that underlies SQL, the most important database language today.
But SQL uses bags, while the relational model is a set-based model.

11. From E/R Diagrams to Relations
Entity sets become relations with the same set of attributes.
Relationships become relations whose attributes are only:
The keys of the connected entity sets.
Attributes of the relationship itself.

12. Entity Set -> Relation
Relation: Beers(name, manf)
name
manf
Beers

13. Relationship -> Relation
name
name
addr
manf
Drinkers
Likes
Likes(drinker, beer)
Beers
Married
husband
wife
Married(husband, wife)
Buddies 1 2
Buddies(name1, name2)
Favorite
Favorite(drinker, beer)

14. Combining Relations
It is OK to combine the relation for an entity-set E with the relation R for a many-one relationship from E to another entity set.
Example: Drinkers(name, addr) and Favorite(drinker, beer) combine to make Drinker1(name, addr, favBeer).

15. Risk with Many-Many Relationships
Combining Drinkers with Likes would be a mistake. It leads to redundancy, as:
name addr beer
Sally 123 Maple Bud
Sally 123 Maple Miller
Redundancy

16. Handling Weak Entity Sets
Relation for a weak entity set must include attributes for its complete key (including those belonging to other entity sets), as well as its own, nonkey attributes.
A supporting (double-diamond) relationship is redundant and yields no relation.

17. Example
name
name
Logins At
Hosts
time

18. Example name name Logins At Hosts time Hosts(hostName)
Logins(loginName, hostName, time)
At(loginName, hostName, hostName2)
At becomes part of
Logins
Must be the same

19. A (Slightly) Formal Definition
A database is a collection of relations (or tables)
Each relation is identified by a name and a list of attributes (or columns)
Each attribute has a name and a domain (or type)
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20. Schema versus instance
Schema (metadata)
Specification of how data is to be structured logically
Defined at set-up
Rarely changes
Instance
Content
Changes rapidly, but always conforms to the schema
Compare to type and objects of type in a programming language
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21. Example Schema Instance
Student (SID integer, name string, age integer, GPA float)
Course (CID string, title string)
Enroll (SID integer, CID integer)
Instance
{ h142, Bart, 10, 2.3i, h123, Milhouse, 10, 3.1i, ...}
{ hCPS116, Intro. to Database Systemsi, ...}
{ h142, CPS116i, h142, CPS114i, ...}
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